Literature DB >> 23890830

Revision total hip and knee arthroplasty implant identification: implications for use of Unique Device Identification 2012 AAHKS member survey results.

Natalia A Wilson1, Megan Jehn2, Sally York3, Charles M Davis4.   

Abstract

FDA's Unique Device Identification (UDI) Rule will mandate manufacturers to assign unique identifiers to their marketed devices. UDI use is expected to improve implant documentation and identification. A 2012 American Association of Hip and Knee Surgeons membership survey explored revision total hip and knee arthroplasty implant identification processes. 87% of surgeons reported regularly using at least 3 methods to identify failed implants pre-operatively. Median surgeon identification time was 20 min; median staff time was 30 min. 10% of implants could not be identified pre-operatively. 2% could not be identified intra-operatively. UDI in TJA registry and UDI in EMR were indicated practices to best support implant identification and save time. FDA's UDI rule sets the foundation for UDI use in patient care settings as standard practice for implant documentation.
© 2013.

Entities:  

Keywords:  implant identification; revision total hip and knee arthroplasty; unique device identification

Mesh:

Year:  2013        PMID: 23890830     DOI: 10.1016/j.arth.2013.06.027

Source DB:  PubMed          Journal:  J Arthroplasty        ISSN: 0883-5403            Impact factor:   4.757


  6 in total

1.  Application of deep learning algorithm in automated identification of knee arthroplasty implants from plain radiographs using transfer learning models: Are algorithms better than humans?

Authors:  Anjali Tiwari; Amit Kumar Yadav; Vaibhav Bagaria
Journal:  J Orthop       Date:  2022-05-26

2.  Automated identification of hip arthroplasty implants using artificial intelligence.

Authors:  Zibo Gong; Yonghui Fu; Ming He; Xinzhe Fu
Journal:  Sci Rep       Date:  2022-07-16       Impact factor: 4.996

3.  Knee Implant Identification by Fine-Tuning Deep Learning Models.

Authors:  Sukkrit Sharma; Vineet Batta; Malathy Chidambaranathan; Prabhakaran Mathialagan; Gayathri Mani; M Kiruthika; Barun Datta; Srinath Kamineni; Guruva Reddy; Suhas Masilamani; Sandeep Vijayan; Derek F Amanatullah
Journal:  Indian J Orthop       Date:  2021-09-28       Impact factor: 1.033

4.  Automated Identification of Orthopedic Implants on Radiographs Using Deep Learning.

Authors:  Ravi Patel; Elizabeth H E Thong; Vineet Batta; Anil Anthony Bharath; Darrel Francis; James Howard
Journal:  Radiol Artif Intell       Date:  2021-03-17

5.  Artificial Intelligence-Based Recognition of Different Types of Shoulder Implants in X-ray Scans Based on Dense Residual Ensemble-Network for Personalized Medicine.

Authors:  Haseeb Sultan; Muhammad Owais; Chanhum Park; Tahir Mahmood; Adnan Haider; Kang Ryoung Park
Journal:  J Pers Med       Date:  2021-05-27

6.  Artificial Intelligence-Based Solution in Personalized Computer-Aided Arthroscopy of Shoulder Prostheses.

Authors:  Haseeb Sultan; Muhammad Owais; Jiho Choi; Tahir Mahmood; Adnan Haider; Nadeem Ullah; Kang Ryoung Park
Journal:  J Pers Med       Date:  2022-01-14
  6 in total

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